In the healthcare industry, significant emphasis is provided to the management of resources. Forecasting and scheduling of resources are the key factors in efficient management of resources. Clinical pathways also referred to as care pathways, critical pathways, integrated care pathways or care maps, represent the sequence of medical procedures for treatment of patients. A clinical pathway is determined based on data gathered from outcome of medical examination and medical diagnostics of a patient.
Various models, based on queuing theory and simulation, are used for forecasting clinical pathways and managing resources in healthcare systems. These models focus on solving resource management problems, analyzing information flows within the healthcare systems, estimating resource requirements and so forth. Further, these models estimate the effect of demographic factors and service characteristics on capacity management in the healthcare systems. These estimates are used for cost reduction and service quality enhancement.
The models based on queuing theory provide solutions for problems with limited data and challenges related to randomness in data. These challenges are solved by making generic assumptions related to various constraints such as length of stay of patients, duration of medical procedures and so forth. The models based on simulation focus on identifying data complexity, identifying distribution of data, validating data, interpreting identified data and so forth.
Some models for forecasting clinical pathways consider patient specific data. For example, clinical pathways forecasted based on initial diagnosis consider the classification from the International Classification of Diseases (ICD) assigned during initial diagnosis of patients.
The models for forecasting clinical pathways and resource requirements have one or more of the following limitations. The models based on queuing theory and simulation do not provide efficient solutions for problems with data complexity. Also, substantial weight is not provided to data collection, data verification and data validation. The models that use ICD data do not consider the patient clinical and diagnostic data, available subsequent to medical procedures, for forecasting clinical pathways, thereby providing incorrect resource requirements forecasts.
Consequently, there is a need for a method and system for efficiently forecasting clinical pathways. Also, the method should enable efficient forecasting of resource requirements. Further, a method and system is required for optimal utilization of resources in healthcare organizations.